Formalisms inspired by Quantum theory have been used in Cognitive Science for decades. Indeed, Quantum-Like (QL) approaches provide descriptive features that are inherently suitable for perception, cognition, and decision processing. A preliminary study on the feasibility of a QL robot perception model has been carried out for a robot with limited sensing capabilities. In this paper, we generalize such a model for multi-sensory inputs, creating a multidimensional world representation directly based on sensor readings. Given a 3-dimensional case study, we highlight how this model provides a compact and elegant representation, embodying features that are extremely useful for modeling uncertainty and decision. Moreover, the model enables to naturally define query operators to inspect any world state, which answers quantifies the robot's degree of belief on that state.
翻译:数十年来,在认知科学中一直使用量子理论所启发的正规主义。 事实上,量子类(QL)方法提供了内在适合感知、认知和决定处理的描述性特征。 已经对一个感知能力有限的机器人进行了关于QL机器人认知模型可行性的初步研究。 在本文件中,我们概括了这种多感知投入模型,直接根据感官读数创建了多层面的世界代表性。 在三维案例研究中,我们强调了这一模型如何提供精细和优雅的描述性特征,体现了对于模拟不确定性和决定极为有用的特征。 此外,该模型还能够自然地界定查询操作者以检查任何世界状态,而这种状态的答案是机器人对该状态的信仰程度的量化。